Longitudinal Changes in Tooth/Single‐Implant Relationship and Bone Topography: An 8‐Year Retrospective Analysis
Bibliographic record
Abstract
PURPOSE: To evaluate longitudinal changes in tooth/implant relationship and bone topography at single implants with a microthreaded, conical marginal portion (Astra Tech ST® implants, Astra Tech AB, Mölndal, Sweden). MATERIAL AND METHODS: Thirty-one subjects with single implant-supported restorations in the esthetic zone were included. Radiographs obtained at crown installation and 1, 5, and 8 years of follow-up were analyzed with regard to changes in (1) bone level at the implant and adjacent teeth and (2) vertical position of adjacent teeth relative to the single implant. RESULTS: The mean marginal bone loss amounted to 0.1 mm at both implants and adjacent teeth during the 8 years of follow-up. Regression analysis failed to identify significant explanatory factors for observed variance in bone level change at the adjacent tooth surfaces. Vertical change in position of the teeth relative to the implants was more frequent and significantly greater in incisor compared with premolar tooth region but not associated with gender or age. CONCLUSIONS: The marginal bone level at teeth adjacent to single implants with a microthreaded conical marginal part was not influenced by horizontal and vertical tooth-implant distances. Continuous eruption of adjacent teeth may result in infraocclusal positioning of a single-implant restoration.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".